About Me
I am a postdoctoral scholar at Stanford Graduate School of Business, where I have the privilege of working with Guido Imbens, Stefan Wager, and Kuang Xu, and collaborating with Ramesh Johari and Airbnb. Previously, I received my Ph.D. degree in Decision, Risk, and Operations from Columbia Business School, where I was very fortunate to be advised by Daniel Russo. My research interests lie at the interface of sequential decision-making under uncertainty and statistical machine learning, including theory and applications of multi-armed bandits, sequential design of experiments, causal inference, and reinforcement learning—with an emphasis on addressing real-world challenges. This mini-course provides an overview of my research. Outside academia, I worked at Scale AI, Google DeepMind, Amazon Web Services AI Lab, and Adobe Research.
Excited to be on the academic job market for the first time in the 2025-2026 cycle!
Contact
Email: chaoqin@stanford.edu
Google Scholar | LinkedIn
Upcoming Events
- Oral presentation, Cornell Young Researchers Workshop, 2025
- Stanford, UC San Diego, and UChicago Rising Stars in Data Science, 2025
- INFORMS Annual Meeting 2025
- SD13 - Learning, Ranking, and Selection
- TB57 - Selected Auctions & Market Design papers from the EC 2025 conference III
- MA22 - Data-Driven Operations, co-organized with Yueyang Liu (Rice Jones Graduate School of Business)
- TE57 - Real-World Experimentation: Bridging Academic Insights and Industry Practice, co-organized with Ramesh Johari (Stanford MS&E) with talks from my collaborators and Airbnb
Selected Past Events
Operations
- Mini-course, Northwestern Kellogg Operations Department, 2025
- Operations seminar, UC Irvine Paul Merage School of Business, 2025
- Guest lecture, Stanford GSB OIT 677: Stochastic Modeling for Data-Driven Decision Making, 2025
- MSOM Technology, Innovation, and Entrepreneurship SIG 2025
- MSOM Service Management SIG 2024
- ISyE-MS&E-IOE Joint Rising Star, 2025
- Spotlight talk, Purdue Supply Chain and Operations Management Conference, 2025
- Conferences including INFORMS, MSOM, APS, RMP, MIW, ICCOPT, as well as a number of internal talks, seminars, and conferences at Stanford and Columbia…
Econometrics, Statistics, and Machine Learning
- Biostatistics seminar, University of California, Berkeley, 2025
- Econometrics seminar, University of Southern California, 2024
- Invited talk, Brown University Bravo Center/SNSF Workshop on Using Data to Make Decisions, 2024
- Spotlight talk, Chicago Booth Machine Learning in Economics Summer Conference (MLESC), 2025
- Oral presentation, Conference on Digital Experimentation @ MIT (CODE@MIT), 2021
- Oral presentation, The 3rd Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM), 2017
- Conferences including ASSA, JSM, SCI-ACIC, NeurIPS, ICML, COLT, EC, CODE@MIT, as well as a number of internal talks, seminars, and conferences at Stanford and Columbia…